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Slowing resource loops in the Circular Economy: an
experimentation approach in fashion retail
Nancy Bocken1, 2, 3*, Karen Miller1, Ilka Weissbrod4, Maria Holgado1, Steve Evans1
1 University of Cambridge, Department of Engineering, Institute for Manufacturing, 17 Charles Babbage
Road, Cambridge CB3 0FS, United Kingdom.
2 Lund University, IIIEE, Tegnérsplatsen 4, 223 50 Lund, Sweden
3 TU Delft, Industrial Design Engineering, Landbergstraat 15, 2628 CE Delft, The Netherlands
4 Imperial College London, Centre for Environmental Policy, Faculty of Natural Sciences, London SW7
1NA, United Kingdom
* nmpb2@cam.ac.uk
Abstract The Circular Economy is viewed as an important driver for resolving
resource issues and tackling sustainability issues more broadly. The fashion
industry operates in a largely linear way and suffers from various environmental,
societal and economic challenges. In a Circular Economy, first and foremost,
products need to be retained at the highest level, thus slowing resource loops.
Slowing resource loops goes against current fast fashion trends and therefore
appears the most difficult approach to pursue. This paper investigates how a large
established retailer aims to slow resource loops as part of a broader project
targeted to significantly reduce textile waste to landfill. The retailer collaborated
with a university partner to pursue circular business model experiments. This paper
reports on the approach for a slowing resource loops experiment around building
sewing capabilities. Suggestions for future research and practice on circular
business model experimentation are included.
1. Background
The Circular Economy has been regarded as a key driver for sustainability
transitions, the concept being promoted by policy-makers, business and academia
[1]. It is an “economic system that replaces the ‘end-of-life’ concept with reducing,
[or] alternatively reusing, recycling and recovering materials in
production/distribution and consumption processes” to accomplish sustainable
development [2]. While there are many ways to depict the circular economy [3] we
summarise the main strategies as closing, slowing and narrowing resource loops
[4, 1]. Slowing loops refers to the design of long-life goods and product-life
extension – the use period of products is extended and/or intensified, resulting in a
slowdown of the flow of resources as it reduces the total need for products [4].
Closing loops is about recycling or closing the loop post (re-)use and production,
resulting in a circular flow of resources and narrowing loops is about efficiencies in
manufacturing and using less material per product, for example through
lightweighting products [4]. In a future circular economy, materials such as textiles
should be maintained at the highest level as long as possible, through business
models that focus on reuse and strategies such as maintenance and repair, service
and warrantees to encourage reuse over time [5]. This requires a substantial shift
in production and consumption patterns and in the role of business in society [6].
The fashion industry in particular has been signified as predominantly linear,
producing vast and growing amounts of waste every year [3]. Clothing production
has doubled in the last 15 years, whereas clothing utilisation (the number of times
a garment is worn) is estimated to have has decreased by 36% [7]. Textiles and
clothing have significant environment and social impact across the life cycle,
ranging from carbon emissions to water, and waste, toxic materials and health and
labour issues [8]. WWF [9] estimated that 2.4% of the world’s crop land is planted
with cotton and that it accounts for 24% and 11% of the global sales of insecticide
and pesticides respectively. Unsafe use of these chemicals has severe health
impacts on workers in the field and on ecosystems [9]. The annual increase in
textile use shows that slowing consumption would be a thorny topic to tackle, but it
can have a significant effect as fibre production dominates clothing’s product life
cycle impacts [10]. An increase of 10% in second hand sales could save 3% in
carbon emissions, 4% in water and 1% in waste [10]. Businesses have
experimented with slower consumption or sufficiency models. For example,
outdoor company Patagonia started experimenting with a zero-growth model and
non-consumerist sales approaches [11].
This paper focuses on experimenting with approaches that facilitate product life
extension in a business context. Experimentation with new business models is
necessary for long-term competitiveness [12] as well transitioning to sustainable
and circular businesses [13]. In particular for difficult topics such as sustainable
consumption and sufficiency which challenges principles of growth [11]
experimentation can be beneficial. For the circular economy to become an
‘environmental success’, experiments to help slow resource loops are needed. This
paper addresses the following question: How can companies start experimenting
with slow consumption as part of their business models?
This paper reports on a large international clothing retailer case. Through a
collaborative project, the company aimed to divert all clothing from landfill through
business model innovations. The paper reports on a business model experiment
that was part of the project. The remainder of the paper is structured as follows.
First, the case study methodology is described. This is followed by a description of
the main project outcomes. The paper then includes a discussion and conclusions.
2. Case study approach
This research explores how companies start experimenting with slow consumption
as part of their business models through a case study with a large international
retailer. The focus is one highlighting some of the key decision-making during the
process by showing the evolvement of ideas using product documentation.
The case study covers a 2.5-year collaborative research project (2014-2016) part
funded by Innovate UK, between a university and an established international
clothing retailer. The project aim was to eliminate clothing waste being disposed to
landfill, using a circular value chain and business model approach for the retailer.
The project aimed to identify pathways to transform the current linear business
model to a more circular one, through business model and supply chain innovation
facilitating recovery and reuse of clothing, using experiments. Slowing resource
loops became the priority of the project with a focus on waste prevention through
clothing reuse. Second, the focus was on how to encourage recycling, thus closing
loops. Finally, another project objective was to learn and develop a circular
business model experimentation capability for future innovation endeavours.
In the project, an experimentation approach was gradually adopted, building on
Lean Startup principles [14, 15] characterised by rapid learning iterations in a low
cost and resource manner [14, 16]. This approach entails quick iterations of
generating ideas, building ‘prototypes’ (e.g. mock websites or paper versions of the
business models [17], measuring impacts, and learning and reiterating). See
Figure 1 for a depiction of this iterative approach. Short learning cycles through
continuous customer testing is key to the Lean Start-up approach [14, 16] and has
long been acknowledged as trait of companies that are able to adapt to changes in
the operating environment [12]. The Lean Startup approach was initially developed
for startups but is now also being applied to large established businesses [14, 16].
Figure 1. Lean startup approach [13, 14, 15]
3. Case study: Slow consumption experimentation at retail
The project sought to develop an intentional and stepwise process, however, in
reality it was mainly emergent and extremely iterative [18] due to the turbulent
nature of the fashion industry and ongoing business pressures from emerging
competition, downward pressures on prices and increasing stakeholder pressures
[20]. Within the project four different overall stages of the circular business model
experimentation process could however be identified: ideating, clustering,
experimenting and refining [18]. Whereas the ideation and clustering phases took
about 2-3 months each, experimentation was the main part of the project, taking
about 10 months. The ideating and clustering phases led to five idea clusters in
total: four focused on extending and retaining the useful life of clothes, and one
focused on recycling used clothing [18]. The focus in this paper is on the “care and
repair” cluster of which “sewing experiments” were a key subtheme. Sewing could
help build awareness about clothing reuse and develop skills and interests around
clothing repair and care. Several other experiments were conducted for the other
four clusters (as well as more for the care and repair cluster), but are beyond the
scope of this study. We report on an experiment that focused on ‘sewing’ and how
the ideas evolved in the project into an experiment.
During each stage (ideating, clustering, experimenting, refining), multiple activities
reoccurred. So, although the process was highly iterative and emergent, some
recurring activities were identified [18]:
1. Gather market, customer and environmental data and prepare analysis (desk
research)
2. Conduct workshops with ideation and engagement and consensus purposes
(involving various stakeholders in and outside the business, such as senior
staff, those who took part in experiments, and NGOs and start-ups)
3. Generate new questions for further analysis (involving various stakeholders)
4. Run experiment and collect further data
To sketch the landscape of the care & repair cluster the template in Table 1 was
developed. It was used to populate all the idea clusters. These templates were a
collection of the considerations taken in the project and were developed in
conjunction with key stakeholders in the business (senior management in
innovation and fashion). These fitted into the ‘desk research’ type of study to
explore the market, environmental benefits and customer traction. It should be
noted that even before the initial ideation workshops, desk research was done to
understand the (recycling) technologies in the fashion industry, potential
environmental initiatives, new startups, market trends etc. This gathering of
supporting data was ongoing throughout the project.
Table 1. Initial idea template to sketch the landscape for the care & repair experiments
1. What is the ‘idea cluster’?
Care & Repair
2. Why is this important?
Work back from ‘ideal’ business model
• Slowing loops
3. What categories might it apply to?
It is already happening here:
• Footwear
• Jeans
Things that easily break/ need repairing:
• Buttons
• Zips
• Hems
• Patches (knee and elbow)
• Moths
Size of the category?
TBC (market study)
4. What are others doing? Who are
competitors?
• Nudie Jeans, Mud Jeans, Patagonia etc.
5. What opportunities could there be for the
company? What value does it create for the
company? What benefit does it create for
the customer?
Company value creation
• Premium branding & reputation for products with
long warrantee
• Footfall & speculative purchasing (e.g. coffees in
coffee/ tea shops)
• Sell the repair service
• Inside and outside warranty difference?
• Pay for refurbishment/ embellishment / tailoring
service with designers
6. What are the challenges we already we
already know about?
• Designed for easy repair or disassembly
• How to make money?
• People have lost the skills and awareness
• Cheap ‘disposable’ clothing
• Infrastructure and network for repairs
• Repair technologies we are not aware of?
7. What are the challenges we want to test
in the pilots?
Tbc (workshop approach)
8. Potential partners?
• Designers (for refurbishing/ embellishing)
• Dry-cleaners & shoe repairers
• Network of tailors (wine masters)
• Great British/ Sewing Bee
9. Adjacent industries to learn from?
• Engineering maintenance
• Car maintenance (annual wardrobe MOT)
• Build-a-bear
Multiple meetings, workshops and further analysis took place. The Lean Startup
idea [14, 16] was introduced more formally into the project after the first
workshops. This led to a focus on developing experiments with key hypotheses
and learning to test. While multiple types of templates were used [18], one of the
key project templates can be found in Figure 2, building on the experiment
templates developed by Osterwalder et al. [19]. This experiment card can be used
by businesses to ‘get on the same page’ before undertaking experiments:
understand the core issues, the hypotheses to test and what to measure. The
experiment card in Figure 2 was populated in preparation for rolling out key
experiments around this theme. As can be seen from Figure 2, the first experiment
aimed to test demand for sewing lessons online, before setting up an experiment in
the retail shop. The population of such cards also consisted of individual work,
followed by meetings with the whole project team.
While this template (as well as others) was important for engagement and
consensus purposes, amongst the project team stakeholders and key stakeholders
in the business (i.e., senior management and those supporting the roll out of
experiments), the selection of an actual experiment was more opportunistic. One of
the industry team members identified an opportunity to become engaged in a
‘sustainability week’ and set up sewing experiments within a shop as part of this
event. This allowed the experiment to take place out in the open but in fact also
‘under the radar’ as part of a normal event. The experiment could build on key
interests and skills of one of the project team members (highly involved in the
sewing community) who understood the needs and opportunities.
Metrics were developed similar to Figure 2 (e.g., whether there was a demand,
which types of lessons, demographics), and observation as well as informal
conversations took place to gather ‘evidence’. Observation sheets were created by
the ‘observers’ (who in fact participated themselves, or were supporting the
coordination of the event) which were then merged into one ‘data document’.
PROJECT(Experiment(Card
HYPOTHESIS
There%is%a%demand%for%lessons%related%to%repair%/%alteration%/%creative%sewing.%The%
association%with%the%company%brand%which%is%known%for%quality,%would%add%
appeal%to%such%lessons.%%
We( bel ie ve( th at :
TEST
Tes t% t he % e xi s ti ng %d e ma nd % f or % se w in g% l e ss on s, % b y% a n al y si ng % on li ne % s ea r c h% tr e nd s. % T hi s% w il l % al s o% in fo rm % g eo gr a ph ic a l%
distribution% of% demand.
Tes t % if % t h e% a s s oc i a t i on % w i t h% t h e %c o m pa n y % br a n d% m i gh t % i n c re a s e % in t e re s t % a nd % t r a ff i c . %T hi s % c a n % be % d on e % b y % p ro d uc i n g% a%
series%of%videos,%potentially%hosted%on%the%the%c ompany%website,%and%compare%click%through%rate %with%similar%non%
branded% videos .
To( v er i f y ( t h a t , (w e ( w i l l:
METRIC
1. The%amount%of%searches%and%click%through%on%registration%pages%
2. Which%types%of%lessons%have%most%demand?%At%which%difficulty%levels?
3. Percentage%of% clic ks%on%the %company ’s%online% videos% vs%avera ge%of%si milar% non%branded
And(measure:
CRITERIA
1.%No%judgement%–we%will%have%a%list%of%the%types%of%lessons%according%to%their%demand
2.%Percentage%on%the%company%w ebsite%lessons% is%significantly%higher% than%percentage% on%mock%we bsite%
We( are (ri gh t( if:
Experiment%name:%Sewing%Lessons%demand%test Experiment%Theme:%Extending%clothes%life
Lead:%XXX% Pre decess or:%Non e%
Key$learnin g$:$Is$th ere$de mand$for$ such$le ssons?$Are $there$ geographic al$areas$ where$de mand$i s$higher?$
PROJECT%Ex periment%Card% Design%adapt ed%from%Oster walder et%al,%2014%-Val ue % Pr opo sit io n% D es ig n: % H ow% t o%C re at e %Pro duc t s% a nd%
Services% Cust omers% Want
Figure 2. Experiment cards used during the project for the Care and Repair theme, later
themed “Extending clothes life”. Building on [18, 19].
Interestingly, eventual decision-making about success or failure of the experiments
happened more intuitively and based on different criteria than those initially set out
by the project team. This occurred as a result of the retailer project team members
having less time than planned to review and revisit the experimentation
documents. Senior Management team members also foreshortened the
experimentation after being briefed on the experiments, accelerating the decision-
making process. The need to make fast decisions and follow up with action may
have been the result of the fast-paced nature of the fashion industry, but there was
also significant enthusiasm within the steering group to be able to try new
propositions for the business in the research project’s context.
The following reflections and lessons can be learned from the process of setting up
a sewing experiment in the retail shop:
1. The process of setting up experiments emerged through phases of
analysis and gathering data in project templates, ideation and
implementation. This process was iterative, involving individual data analysis,
multiple meetings within the project team followed by engagement with key
stakeholders in the business, and finally implementation in a shop. Because of
the nature of ‘large business’, and the need to set up experiments in a
turbulent business environment, it was felt that this process took much longer
than it would have in a startup environment.
2. Initial hypotheses were formulated but eventually all types of learning
were tracked. Similar to the broader ‘metrics’ in Table 1, the broader context
and business benefits of doing a sewing experience in a large retail shop were
evaluated. For example, does it fit with the brand? Does it create new
opportunities for the company? The observations and conversations with
participants as well as interest from shoppers passing-by, indicated a real
engagement with sewing, repairing and looking after clothes and the
environment. Another reason for the felt need to track all kinds of learning may
originate from the fact that the company could ‘finally’ test a novel business
model direction out in the open.
3. Decision-making became intuitive, rather than formalised. Specific
hypotheses were formulated for the sewing experiments. However, the shop
manager who was not part of the project team, became so enthusiastic
because of the success of the event (customer traction, positive responses
from the public), that it resulted in the retail shop running more such events.
This had further spill-over effects with more the events in other parts of the
country. At the time of writing, nine further ‘sewing events’ had taken place in
retail shops. In large business contexts decision-making may be more complex
and dispersed [20], and ideas may be accepted or rejected unexpectedly. This
may be positive, when an experiment has failed the hypotheses test, but gets
embedded because of other reasons (e.g. footfall in store; building the brand).
It was found that project documentation and data analysis do support
engagement and consensus making about which experiments to pursue, but
decisions may be made more intuitively and in unexpected ways.
4. Environmental impact improvement is difficult to derive from single
experiments. Businesses may have ‘environmental value propositions’ in mind
when designing the business model [21] and indeed an environmental intent
was described for each of the ideas (Table 1). Nevertheless, the actual impact
of business model innovation, in particular those aimed at longer product life
times and slowing resource loops, may only be felt over a longer period of
time. Hence, it is important to keep track of progress against such goals (e.g.
prevented waste, recycling rates etc.).
5. Slow consumption is (evidently) a challenging topic in fast fashion. ‘Slow
consumption’ in a highly competitive environment with downward pressures on
prices is a difficult concept in particular with senior management who are under
pressure to deliver to short-term sales targets [20]. Whereas in the project,
companies like Patagonia were often mentioned as examples of sufficiency, it
was felt that it was difficult for the company to undergo such a radical
transformation to a more premium-priced business model, which in theory
could justify slower flows of fashion. It should be noted that ‘slow consumption’
was also absent as a strategy from the recent Ellen MacArthur Foundation [7]
report on circular economy for the textiles industry, indicating it remains a
demanding topic. Nevertheless, new models would need to be explored to
slow resource use (e.g. more premium, charging for services etc.).
6. Experimentation can accelerate new sustainable business activity. As an
overall reflection of the process, the project generated new activity and
adoption of an innovation and learning approach based on experimentation: in
interviews which took place after concluding the project it was noted by the
project coordinator that ‘expectations had been surpassed’ as typically ‘it is
difficult to make stuff happen in a large business’ [18]. New propositions were
tested and rolled out, and others were trialed with niche customers. Success
was thus defined as the new experimentation approach being adopted and
new business activity and transformation taking place in the business.
4. Discussion and conclusions
This paper explored the following question by means of a company case of an
international fashion retailer: How can companies start experimenting with slow
consumption as part of their business models?
The case study presented an example of the emergence of an experiment to test
the interest in sewing lessons in a shop, with the ultimate goal to make people
more environmentally conscious about clothing (re)use and (re)building skills and
interests in repair and care for clothes. The process to develop experiments was
described, and included an analysis phase (e.g. market, customer and
environmental data), workshop phase for ideation, engagement and consensus,
generating new questions for analysis and running experiments and collecting
further data. Templates were included that could support experimentation
processes in other large business contexts. It was found that:
1. The process of setting up experiments emerged through phases of analysis
and gathering data in project templates, ideation and implementation.
2. Initial hypotheses were formulated but eventually all types of learning were
tracked.
3. Decision-making became intuitive, rather than formalised.
4. Environmental impact improvement is difficult to derive from single
experiments.
5. Slow consumption is (evidently) a challenging topic in fast fashion.
6. Experimentation can accelerate new sustainable business activity.
This study shows that the process of experimentation for circularity and
sustainability in a large business context remains a promising avenue for future
research as it can spark new activities and practices, which are at the heart of
sustainability transitions [22]. While decision-making may seem ‘rigid’ and
formalised in large business, it was found that the tangible real-life context
evidence that experiments bring may help accelerate and fast-track decision-
making. Important other research areas relate to tracking environmental impact
improvements in sustainable and circular business model innovation; identifying
ways to slow resource loops; and developing slow consumption into viable
business model strategies.
Acknowledgements
This work was supported by the EPSRC Centre for Innovative Manufacturing in
Industrial Sustainability (Reference EP/I033351/1); the Innovate UK competition
‘Supply Chain Innovation towards a Circular Economy’ (IUK Ref 101902); and
Climate-KIC, the public-private partnership created by the European Institute of
Innovation and Technology (Regulation (EU) No 1292/2013).
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